IBM Cloud Pak for Data V4.x Data Engineer Practice Exam 2025: Latest Questions

A data engineer needs to understand which Cloud Pak for Data capability provides a web-based interface to run notebooks, manage runtime environments, and execute code against data services. Which capability should be used?

A team needs to integrate data from multiple operational databases into an analytics-ready target. They want a visual, scheduled ETL tool with connectors, jobs, and parallel execution. Which service best fits this requirement?

An organization wants users to easily find trusted datasets, view business terms, and understand how data is classified. Which Cloud Pak for Data component is primarily responsible for this?

A business analyst wants to run a single SQL query that joins a table in Db2 with a table in an external data source without physically moving the data first. What capability should be used?

A DataStage job fails when writing to the target due to data type mismatches between source and target columns. What is the best approach to prevent this failure in a reusable way?

A platform admin needs to explain the purpose of Cloud Pak for Data "projects" to a new team. Which statement best describes a project?

A governed dataset must only be visible to members of the Finance group, and access should be managed consistently across catalog users. Which approach best meets this requirement?

A data engineer virtualizes a table from an external source and notices slow queries due to repeated remote scans. They need to improve performance while keeping the data source authoritative. What is the best next step?

A company needs end-to-end traceability for a curated dataset: where it originated, which transformations were applied, and which downstream assets consume it. Which combination best supports this requirement in Cloud Pak for Data?

A DataStage job reads from multiple sources and writes to several targets. The team wants to re-run the job safely after a failure without creating duplicates or partial loads. Which design is the best practice to achieve this?

A data engineer is onboarding a new project to Cloud Pak for Data and wants teams to build pipelines in a governed way with reusable assets and consistent connections. Which approach is the BEST fit?

A pipeline built with DataStage fails when writing to a target because it cannot locate the connection details after the connection password was rotated. What is the MOST likely cause?

A business user needs to find trusted datasets across multiple projects and understand who owns them, their meaning, and how they should be used. Which capability should be used?

A team wants analysts to query multiple data sources with a single SQL endpoint without copying data, and they need to control access at the virtual layer. Which solution is MOST appropriate?

A data engineer needs to design a nightly ETL process that loads fact and dimension tables, ensuring dimensions are updated before facts and that failures trigger notifications. Which design is MOST appropriate?

A catalog curator wants to prevent sensitive columns (e.g., SSN) from being visible to most users while still allowing discovery of the dataset. What is the BEST approach?

A Data Virtualization query that joins large tables across two remote sources is slow. The engineer wants to improve performance without permanently copying all data into a warehouse. What should they do FIRST?

A project requires traceability from raw source ingestion through transformations to curated tables so auditors can understand how a metric was produced. Which capability should be used to provide this end-to-end traceability?

A company has multiple teams creating virtual views in Data Virtualization. They want a controlled promotion process from development to production with minimal disruption and clear ownership. Which approach is MOST appropriate?

A DataStage job reads from an object storage file that sometimes arrives late. The job fails when the file is missing, causing the entire nightly pipeline to fail. What is the BEST design to handle this scenario?

A data engineer needs to run a Spark-based transformation that requires cluster resources and must be scheduled to run nightly within Cloud Pak for Data. Which component is the best fit to author and run this Spark workload?

A team uses DataStage to load data from an object storage landing zone into curated tables. They want to prevent partial loads when a job fails mid-run and ensure the curated tables only reflect fully successful runs. Which approach is the best practice?

A dataset is cataloged in Watson Knowledge Catalog and includes a "PII" classification. A consumer searches for the asset and can see its metadata, but is prevented from viewing or downloading the data. Which control most directly enforces this behavior?

A user creates a virtual table in Data Virtualization that joins a remote relational database with a local curated table. Queries are slow, and the remote source team reports high load due to repeated scans. What is the best way to improve performance while reducing impact on the remote source?

A DataStage job reads from a relational source via JDBC. In development it succeeds, but in production it fails immediately with an authentication error even though the same username/password works when tested from another tool. The production environment uses Cloud Pak for Data managed credentials. What is the most likely cause and the best fix?